Development and use of new and derived data to facilitate the optimisation and evaluation of breast screening AI tools

This PhD project will use techniques to alter an unprocessed image to make it appear as if it was captured with lower dose or different beam quality or x-ray detector, or processed using different manufactures image processing software to generate additional data to supplement OMI-DB. It will also develop image processing software to understand the effect of this on the images that are used for AI tool development. This project will involve the use of this data to investigate and evaluate how varying factors in the images may confound or affect an AI tools performance. This will involve retraining in-house algorithms and subsequent validation to evaluate the resulting effects that varying the training and validation datasets have. Is it anticipated that in addition to the use of in-house or open-source algorithms the project will involve utilising the groups' existing collaboration with Google Health to investigate these same factors in the Google Health Breast AI tool.

This project will develop physics-based methodology to derive new data to assess AI based tools for medical imaging. This requires the development of new knowledge and fundamental research in a way which is well-suited to a PhD project. The project brings together metrological analysis and data science skills with medical imaging, and involves working with specialists from several different disciplines, preparing the candidate for a career in either medical research or data-intensive metrology.